TAILIEUCHUNG - Artificial Intelligence for Wireless Sensor Networks Enhancement Part 4

Tham khảo tài liệu 'artificial intelligence for wireless sensor networks enhancement part 4', kỹ thuật - công nghệ, cơ khí - chế tạo máy phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | Artificial Intelligence for Wireless Sensor Networks Enhancement 79 Capturing Agent of physical variables CA It is a mobile agent that is aware of physical variables according to a specific application. It takes decisions about propagation and transmitting of these variables. Application Layer The application layer represents specific study case or application for which the WSN is going to be deployed. Therefore this layer has agents that perform application required tasks. Coordinator Agent CoA It is an agent aware of required tasks by a study case so it has a queue of application tasks. Hence it manages organizes and negotiates them for being executed by a TA successfully. Also it takes decisions based on a BDI model. Tasks Agent TA It is a reactive agent that performs tasks assigned by a CoA as long as CoA said it had to be. Deliberative Agent DA It is a mobile agent that takes decisions based on a BDI model too. It does not need that a CoA manages organizes and negotiates its tasks it does by its own. Accordingly it performs a set of tasks to achieve its own goal or a goal established by a MAS which it belongs to. It is a specific treatment for an application multi-agent system due to not all sensor nodes platforms can perform a rational agent . for a simple application there is a group of TA with a CoA that manages and coordinates entire system and for a complex application there is a group of DA that interact to achieve a global goal. Interaction Process First of all the CoA or a DA depending of required type agents starts the process for assigning a task it has the belief that a task needs to be done it has this belief because there is a tasks list related to the application. Its desire consist of ensure that a task is done successfully by a TA. Then its first intention is to interact with MA and to ask task feasibility. Now MA beliefs about its hardware characteristics and charge task and its desire consist to inform if there are enough .

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